Obviously, the size of your 3D print is limited to the size of your 3D printer…you wouldn’t try and 3D print a building, no matter how small, using a desktop system, right? Jace J. McPherson from the University of Arkansas put it more exactly in the honor’s thesis he wrote and submitted for his Bachelor’s degree in Computer Science and Computer Engineering:
“More specifically, an object cannot be printed if it is wider than the full horizontal movement range of an extrusion nozzle or if it is taller than the maximum height of the extrusion nozzle above the printing surface (i.e., the “print bed”).”
According to McPherson’s thesis, titled “A Scalable, Chunk-based Slicer for Cooperative 3D Printing,” print jobs’ size limitations can hinder the technology’s goal of being “fully dynamic.” In the thesis, he focused on the issue of 3D printer scalability – limited by print bed size and use of a single printhead – and lack of manufacturing automation, and the idea of cooperative 3D printing, and a new slicing strategy for this technology, as a combined solution.
The abstract states, “Cooperative 3D printing is an emerging technology that aims to increase the 3D printing speed and to overcome the size limit of the printable object by having multiple mobile 3D printers (printhead-carrying mobile robots) work together on a single print job on a factory floor. It differs from traditional layer-by-layer 3D printing due to requiring multiple mobile printers to work simultaneously without interfering with each other. Therefore, a new approach for slicing a digital model and generating commands for the mobile printers is needed, which has not been discussed in literature before. We propose a chunk-by-chunk based slicer that divides an object into chunks so that different mobile printers can print different chunks simultaneously without interfering with each other. In this paper, we first developed a slicer for cooperative 3D printing with two mobile fused deposition modeling (FDM) printers. To enable many more mobile printers working together, we then developed a framework for scaling to many mobile printers with high parallel efficiency. To validate our slicer for the cooperative 3D printing process, we have also developed a simulator environment, which can be a valuable tool in visualizing and optimizing a cooperative 3D printing strategy. This simulation environment was also developed to export the visualization in a generic format for use elsewhere.”
Cooperative 3D printing is made up of multiple independent, free-roaming robot 3D printers that receive instructions on how to print one part, or chunk, of a whole object. The mechanism makes it possible to autonomously complete large print jobs, with no interruptions, in a single piece, without human interaction. The parts are actually 3D printed on top of each other so they’re joined during the process and not after.
“Cooperative 3D printing solves physical scalability with the premise that multiple independent 3D printers can be used to produce a single object. These printers need to “cooperate” to produce objects that would normally exceed the size limitation of a traditional 3D printer. They must have the freedom to navigate a large area, such that their print range is limited only by the size of the print surface, as opposed to a fixed range imposed by the extrusion nozzle’s mechanism. To summarize, assuming the print surface is easy to scale, the potential print size will also be highly scalable,” McPherson wrote.
“This new mechanism also solves time scalability assuming new 3D printers that enter the fray can decrease the overall print time. Given that the number of printers is dynamic, we can quantify the time scalability as a function of the parallel efficiency from using any number of robots.”
The chunker design subdivides 3D models into chunks, which are then split up between the robots for 3D printing. The slicer converts these chunks into print commands for the robots, and the simulator creates a visual, using the slicer commands, that shows how real robots would complete their tasks. It’s important for the simulator to be properly designed, as it’s used to validate the chunker and slicer algorithms – if the simulator is not accurate, the rest of the process isn’t either.
In the rest of his thesis, McPherson describes how the slicer makes it possible to subdivide models so that chunks can be 3D printed in parallel, as well as demonstrating how to scale the slicer for more than two robots for additional degrees of spatial freedom.
“Results show that the developed slicer and simulator are working effectively,” McPherson wrote.
McPherson hopes that this project can help “lay the foundation for scalable Cooperative 3D printing,” which could open up a whole new direction of research for scaling 3D printing, and potentially even “revolutionize the way manufacturing processes are structured.”
“This thesis has presented, in detail, a feasible process for managing 𝑁𝑁 3D printing robots operating in parallel on a single print job, taking into account the geometric constraints, the communication requirements between robots, and the necessary pre-processing needed to properly subdivide a model for chunk-based printing,” McPherson concluded.
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